Studying Tumor Tissue Samples From Patients With Early-Stage Non-Small Cell Lung Cancer

Overview

This research trial studies biomarkers in predicting the risk of cancer returning after surgery in tissue samples of patients with early-stage non-small cell lung cancer. Studying samples of tumor tissue from patients with cancer in the laboratory may help doctors identify and learn more about biomarkers related to cancer and predict how well patients will respond to treatment.

PRIMARY OBJECTIVES: I. To develop and validate a clinically useful molecular prognostic signature based on ribonucleic acid (RNA)-expression arrays to accurately distinguish between good and poor outcome in patients with stage 1B non-small cell lung cancer (NSCLC) (T2aN0M0) by predicting the risk of cancer recurrence after surgery. SECONDARY OBJECTIVES: I. To develop and validate a clinically useful prognostic signature for stage 1A NSCLC (T1a-bN0M0) that accurately predicts the risk of post-operative cancer recurrence and is part of a prognostic classifier, which also includes histological, pathological, and demographic parameters as in the primary objective. II. To determine the effects on test accuracy of the histological subtype (adenocarcinoma \[AC\] vs squamous cell \[SQA\]) for each of the stage specific prognostic classifiers. III. To determine the relevant statistical features, including accuracy of predicting overall survival, cancer specific survival, and disease free survival at 3 and 5 years, for each of the prognostic classifiers validated. IV. To utilize the validated prognostic signatures and classifiers in stage 1B NSCLC to determine whether these can reliably predict good outcome among stage II NSCLC patients. OUTLINE: RNA extracted from archived tumor tissue samples are analyzed for whole-genome expression by Affymetrix microarrays (Gene Profiling Array cGMP U133 P2) and reverse transcriptase-polymerase chain reaction (RT-PCR).

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Eligibility

Locations (1)

Outcomes